Reinforcement learning's (RL) objective is to develop agents able to learn optimal policies in unknown environments by trial-and-error and with limited supervision. Recent developments in exploration-exploitation, online learning, planning, and representation learning are making RL more and more appealing to real-world applications, with promising results in challenging domains such as recommendation systems, computer games, and robotics.

The 12th edition of EWRL will be co-located with the ICML workshops and it will serve as a forum to discuss the state-of-the-art and future research directions and opportunities for the growing field of RL. We intend to make this an exciting event not only for the European RL community but also international researchers from related areas with many opportunities to share new knowledge and encourage collaborative work. Beyond traditional topics, we will encourage discussions on representation learning, risk-averse learning, apprenticeship and transfer learning, and practical applications.

We are calling for papers from the entire reinforcement learning spectrum, with the option of either 2-page short papers or longer 8-page JMLR format research papers. We will publish selected papers in the prestigious Proceedings of Machine Learning Research (the JMLR W&C series). Double submissions are allowed but must be clearly indicated. However in the event that an EWRL paper is accepted to another conference proceedings or journal, it will not be reprinted in the official EWRL proceedings. The paper would still be considered, however, for acceptance and presentation at EWRL.

We encourage submissions from a range of topics including (but not limited to):